Consumers are at a serious negotiation disadvantage when they do not have information relevant to a specifically desired product or do not understand such information. Exacerbating this problem is the fact that complex, negotiated transactions can be difficult for consumers to understand due to a variety of factors, including interdependence between local demand and availability of products or product features, the point-in-time in the product lifecycle at which a transaction occurs, and the interrelationships of various transactions to one another. For example, a seller may sacrifice margin on one aspect of one transaction and recoup that margin from another transaction with the same (or a different) customer. Furthermore, currently available data for complex transactions is single dimensional. To illustrate with a specific example, a recommended price (e.g. $1,000) may not take into account how sensitive that price is (is $990 a good or bad price)? Recommended prices also become decreasingly accurate as the product, location, and availability of a particular product is defined with greater specificity.
These circumstances can be seen in a variety of contexts. In particular, the automotive transaction process may entail complexity of this type. Specifically, the price a consumer pays may depend on the vehicle, the dealership, historical patterns, anticipated sales patterns, promotion programs, the customer's and dealer's emotions on a particular day, the time of the day, the day of the month, and the dynamics of the negotiation itself, and so on. Often times, neither the consumers nor the dealers can fully understand what a good or great price is for a certain vehicle having a particular combination of make, model, trim combinations or packages, etc. Additionally, even though new vehicles are commodities, transparent pricing information resources for consumers simply do not exist. Some dealers attempt to optimize or maximize pricing from each individual customer through the negotiation process which inevitably occurs with customers in the setting of an automotive vehicle purchase.
There are therefore a number of unmet desires when it comes to obtaining, analyzing and presenting vehicle pricing data.